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Adaptive Signal Processing

NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY


We propose a novel problem formulation for sparsity-aware adaptive filtering based on the nonconvex minimax concave (MC) penalty, aiming to obtain a sparse solution with small estimation bias. We present two algorithms: the first algorithm uses a single firm-shrinkage operation, while the second one uses double soft-shrinkage operations. The twin soft-shrinkage operations compensate each other, promoting sparsity while avoiding a serious increase of biases. The whole cost function is convex in certain parameter settings, while the instantaneous cost function is always nonconvex.

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Authors:
Hiroyuki Kaneko, Masahiro Yukawa
Submitted On:
15 May 2020 - 8:00pm
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[1] Hiroyuki Kaneko, Masahiro Yukawa, "NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5360. Accessed: Jul. 09, 2020.
@article{5360-20,
url = {http://sigport.org/5360},
author = {Hiroyuki Kaneko; Masahiro Yukawa },
publisher = {IEEE SigPort},
title = {NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY},
year = {2020} }
TY - EJOUR
T1 - NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY
AU - Hiroyuki Kaneko; Masahiro Yukawa
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5360
ER -
Hiroyuki Kaneko, Masahiro Yukawa. (2020). NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY. IEEE SigPort. http://sigport.org/5360
Hiroyuki Kaneko, Masahiro Yukawa, 2020. NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY. Available at: http://sigport.org/5360.
Hiroyuki Kaneko, Masahiro Yukawa. (2020). "NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY." Web.
1. Hiroyuki Kaneko, Masahiro Yukawa. NORMALIZED LEAST-MEAN-SQUARE ALGORITHMS WITH MINIMAX CONCAVE PENALTY [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5360

Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters


Altitude estimation is important for successful control and navigation of unmanned aerial vehicles (UAVs). UAVs do not have indoor access to GPS signals and can only use on-board sensors for reliable estimation of altitude. Unfortunately, most existing navigation schemes are not robust to the presence of abnormal obstructions above and below the UAV.

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Authors:
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo
Submitted On:
14 May 2020 - 8:35pm
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[1] Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo, "Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5327. Accessed: Jul. 09, 2020.
@article{5327-20,
url = {http://sigport.org/5327},
author = {Liu Yang; Hechuan Wang; Yousef El-Laham; José Fonte; David Pérez; Mónica F. Bugallo },
publisher = {IEEE SigPort},
title = {Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters},
year = {2020} }
TY - EJOUR
T1 - Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters
AU - Liu Yang; Hechuan Wang; Yousef El-Laham; José Fonte; David Pérez; Mónica F. Bugallo
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5327
ER -
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. (2020). Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters. IEEE SigPort. http://sigport.org/5327
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo, 2020. Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters. Available at: http://sigport.org/5327.
Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. (2020). "Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters." Web.
1. Liu Yang, Hechuan Wang, Yousef El-Laham, José Fonte, David Pérez, Mónica F. Bugallo. Indoor Altitude Estimation of Unmanned Aerial Vehicles Using a Bank of Kalman Filters [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5327

Feature Affine Projection Algorithms


There is a growing research interest in proposing new techniques to detect and exploit signals/systems sparsity. Recently, the idea of hidden sparsity has been proposed, and it has been shown that, in many cases, sparsity is not explicit, and some tools are required to expose hidden sparsity. In this paper, we propose the Feature Affine Projection (F-AP) algorithm to reveal hidden sparsity in unknown systems. Indeed, first, the hidden sparsity is revealed using the feature matrix, then it is exploited using some sparsity-promoting penalty function.

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Authors:
Hamed Yazdanpanah
Submitted On:
3 May 2020 - 10:10pm
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[1] Hamed Yazdanpanah, "Feature Affine Projection Algorithms", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5119. Accessed: Jul. 09, 2020.
@article{5119-20,
url = {http://sigport.org/5119},
author = {Hamed Yazdanpanah },
publisher = {IEEE SigPort},
title = {Feature Affine Projection Algorithms},
year = {2020} }
TY - EJOUR
T1 - Feature Affine Projection Algorithms
AU - Hamed Yazdanpanah
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5119
ER -
Hamed Yazdanpanah. (2020). Feature Affine Projection Algorithms. IEEE SigPort. http://sigport.org/5119
Hamed Yazdanpanah, 2020. Feature Affine Projection Algorithms. Available at: http://sigport.org/5119.
Hamed Yazdanpanah. (2020). "Feature Affine Projection Algorithms." Web.
1. Hamed Yazdanpanah. Feature Affine Projection Algorithms [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5119

DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS


The huge volume of data that are available today requires data-
selective processing approaches that avoid the costs in computa-
tional complexity via appropriately treating the non-innovative data.
In this paper, extensions of the well-known adaptive filtering LMS-
Newton and LMS-Quasi-Newton Algorithms are developed that
enable data selection while also addressing the censorship of out-
liers that emerge due to high measurement errors. The proposed
solutions allow the prescription of how often the acquired data are

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Authors:
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14 May 2019 - 5:42am
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[1] , "DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4505. Accessed: Jul. 09, 2020.
@article{4505-19,
url = {http://sigport.org/4505},
author = { },
publisher = {IEEE SigPort},
title = {DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS},
year = {2019} }
TY - EJOUR
T1 - DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4505
ER -
. (2019). DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS. IEEE SigPort. http://sigport.org/4505
, 2019. DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS. Available at: http://sigport.org/4505.
. (2019). "DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS." Web.
1. . DATA-SELECTIVE LMS-NEWTON AND LMS-QUASI-NEWTON ALGORITHMS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4505

A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties


Stochastic mirror descent (SMD) algorithms have recently garnered a great deal of attention in optimization, signal processing, and machine learning. They are similar to stochastic gradient descent (SGD), in that they perform updates along the negative gradient of an instantaneous (or stochastically chosen) loss function. However, rather than update the parameter (or weight) vector directly, they update it in a "mirrored" domain whose transformation is given by the gradient of a strictly convex differentiable potential function.

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Authors:
Navid Azizan, Babak Hassibi
Submitted On:
13 May 2019 - 8:33pm
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[1] Navid Azizan, Babak Hassibi, "A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4498. Accessed: Jul. 09, 2020.
@article{4498-19,
url = {http://sigport.org/4498},
author = {Navid Azizan; Babak Hassibi },
publisher = {IEEE SigPort},
title = {A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties},
year = {2019} }
TY - EJOUR
T1 - A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties
AU - Navid Azizan; Babak Hassibi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4498
ER -
Navid Azizan, Babak Hassibi. (2019). A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties. IEEE SigPort. http://sigport.org/4498
Navid Azizan, Babak Hassibi, 2019. A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties. Available at: http://sigport.org/4498.
Navid Azizan, Babak Hassibi. (2019). "A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties." Web.
1. Navid Azizan, Babak Hassibi. A Characterization of Stochastic Mirror Descent Algorithms and Their Convergence Properties [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4498

Analysis of Broadband GEVD-Based Blind Source Separation

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Authors:
Jen Pestana, Soydan Redif
Submitted On:
8 May 2019 - 5:18am
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[1] Jen Pestana, Soydan Redif, "Analysis of Broadband GEVD-Based Blind Source Separation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4055. Accessed: Jul. 09, 2020.
@article{4055-19,
url = {http://sigport.org/4055},
author = {Jen Pestana; Soydan Redif },
publisher = {IEEE SigPort},
title = {Analysis of Broadband GEVD-Based Blind Source Separation},
year = {2019} }
TY - EJOUR
T1 - Analysis of Broadband GEVD-Based Blind Source Separation
AU - Jen Pestana; Soydan Redif
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4055
ER -
Jen Pestana, Soydan Redif. (2019). Analysis of Broadband GEVD-Based Blind Source Separation. IEEE SigPort. http://sigport.org/4055
Jen Pestana, Soydan Redif, 2019. Analysis of Broadband GEVD-Based Blind Source Separation. Available at: http://sigport.org/4055.
Jen Pestana, Soydan Redif. (2019). "Analysis of Broadband GEVD-Based Blind Source Separation." Web.
1. Jen Pestana, Soydan Redif. Analysis of Broadband GEVD-Based Blind Source Separation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4055

l0-norm Feature LMS Algorithms


A class of algorithms known as feature least-mean-square (FLMS) has been proposed recently to exploit hidden sparsity

Paper Details

Authors:
Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima
Submitted On:
16 November 2018 - 4:29pm
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[1] Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima, "l0-norm Feature LMS Algorithms", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3671. Accessed: Jul. 09, 2020.
@article{3671-18,
url = {http://sigport.org/3671},
author = {Hamed Yazdanpanah; José Antonio Apolinário Jr.; Paulo Sergio Ramirez Diniz; Markus Vinicius Santos Lima },
publisher = {IEEE SigPort},
title = {l0-norm Feature LMS Algorithms},
year = {2018} }
TY - EJOUR
T1 - l0-norm Feature LMS Algorithms
AU - Hamed Yazdanpanah; José Antonio Apolinário Jr.; Paulo Sergio Ramirez Diniz; Markus Vinicius Santos Lima
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3671
ER -
Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima. (2018). l0-norm Feature LMS Algorithms. IEEE SigPort. http://sigport.org/3671
Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima, 2018. l0-norm Feature LMS Algorithms. Available at: http://sigport.org/3671.
Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima. (2018). "l0-norm Feature LMS Algorithms." Web.
1. Hamed Yazdanpanah, José Antonio Apolinário Jr., Paulo Sergio Ramirez Diniz, Markus Vinicius Santos Lima. l0-norm Feature LMS Algorithms [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3671

Distributed Inference over Multitask Graphs under Smoothness

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23 June 2018 - 8:45am
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[1] , "Distributed Inference over Multitask Graphs under Smoothness", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3312. Accessed: Jul. 09, 2020.
@article{3312-18,
url = {http://sigport.org/3312},
author = { },
publisher = {IEEE SigPort},
title = {Distributed Inference over Multitask Graphs under Smoothness},
year = {2018} }
TY - EJOUR
T1 - Distributed Inference over Multitask Graphs under Smoothness
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3312
ER -
. (2018). Distributed Inference over Multitask Graphs under Smoothness. IEEE SigPort. http://sigport.org/3312
, 2018. Distributed Inference over Multitask Graphs under Smoothness. Available at: http://sigport.org/3312.
. (2018). "Distributed Inference over Multitask Graphs under Smoothness." Web.
1. . Distributed Inference over Multitask Graphs under Smoothness [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3312

Distributed Inference over Multitask Graphs under Smoothness

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23 June 2018 - 8:45am
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[1] , "Distributed Inference over Multitask Graphs under Smoothness", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3311. Accessed: Jul. 09, 2020.
@article{3311-18,
url = {http://sigport.org/3311},
author = { },
publisher = {IEEE SigPort},
title = {Distributed Inference over Multitask Graphs under Smoothness},
year = {2018} }
TY - EJOUR
T1 - Distributed Inference over Multitask Graphs under Smoothness
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3311
ER -
. (2018). Distributed Inference over Multitask Graphs under Smoothness. IEEE SigPort. http://sigport.org/3311
, 2018. Distributed Inference over Multitask Graphs under Smoothness. Available at: http://sigport.org/3311.
. (2018). "Distributed Inference over Multitask Graphs under Smoothness." Web.
1. . Distributed Inference over Multitask Graphs under Smoothness [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3311

Identification of Bilinear Forms with the Kalman Filter

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Authors:
Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida
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21 April 2018 - 12:05pm
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[1] Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida, "Identification of Bilinear Forms with the Kalman Filter", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3123. Accessed: Jul. 09, 2020.
@article{3123-18,
url = {http://sigport.org/3123},
author = {Laura Dogariu; Constantin Paleologu; Silviu Ciochina; Jacob Benesty; Pablo Piantanida },
publisher = {IEEE SigPort},
title = {Identification of Bilinear Forms with the Kalman Filter},
year = {2018} }
TY - EJOUR
T1 - Identification of Bilinear Forms with the Kalman Filter
AU - Laura Dogariu; Constantin Paleologu; Silviu Ciochina; Jacob Benesty; Pablo Piantanida
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3123
ER -
Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida. (2018). Identification of Bilinear Forms with the Kalman Filter. IEEE SigPort. http://sigport.org/3123
Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida, 2018. Identification of Bilinear Forms with the Kalman Filter. Available at: http://sigport.org/3123.
Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida. (2018). "Identification of Bilinear Forms with the Kalman Filter." Web.
1. Laura Dogariu, Constantin Paleologu, Silviu Ciochina, Jacob Benesty, Pablo Piantanida. Identification of Bilinear Forms with the Kalman Filter [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3123

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